Modeling human auditory evoked brainstem responses based on nonlinear cochlear processing

James Harte, Filip Munch Rønne, Torsten Dau

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

175 Downloads (Pure)


The aim of this study was to accurately simulate auditory evoked potentials (AEPs) from various classical stimuli such
as clicks and tones, often used in research and clinical diagnostics. In an approach similar to Dau (2003), a model
was developed for the generation of auditory brainstem responses (ABR) to transient sounds and frequency following
responses (FFR) to tones. The model includes important cochlear processing stages (Zilany and Bruce, 2006) such
as basilar-membrane (BM) tuning and compression, inner hair-cell (IHC) transduction, and IHC auditory-nerve (AN)
synapse adaptation. To generate AEPs recorded at remote locations, a convolution was made on an empirically obtained
elementary unit waveform with the instantaneous discharge rate function for the corresponding AN unit. AEPs to
click-trains, as well as to tone pulses at various frequencies, were both modelled and recorded at different stimulation
levels and repetition rates. The observed nonlinearities in the recorded potential patterns, with respect to ABR wave
V latencies and amplitudes, could be largely accounted for by level-dependent BM processing as well as effects of
short-term neural adaptation. The present study provides further evidence for the importance of cochlear tuning and AN
adaptation on AEP patterns, and provides a useful basis for the study of more complex stimuli including speech.
Original languageEnglish
Title of host publicationProceedings of the 20th International Congress on Acoustics
Publication date2010
Publication statusPublished - 2010
Event20th International Congress on Acoustics - Sydney, Australia
Duration: 23 Aug 201027 Aug 2010


Conference20th International Congress on Acoustics


Dive into the research topics of 'Modeling human auditory evoked brainstem responses based on nonlinear cochlear processing'. Together they form a unique fingerprint.

Cite this